Simulation and Modelling - Syllabus

An overview of computers and their significance in today's world. This topic sets the stage for understanding the basics of computers.

Understanding the difference between digital and analog computers, their characteristics, and applications.

Exploring the key characteristics of computers, including input, processing, storage, and output.

A brief history of computers, from their inception to the present day, highlighting key milestones and developments.

Understanding the different generations of computers, including their features, advantages, and limitations.

Categorizing computers based on their size, functionality, and application, including desktops, laptops, and mobile devices.

An in-depth look at the components of a computer system, including hardware and software.

Exploring the various applications of computers in different fields, including business, education, and healthcare.

Understanding the legal framework governing E-commerce in Nepal.

This topic explores the various application areas of simulation, including engineering, economics, and healthcare.

Overview of software tools used for simulation, including their features and applications.

Introduction to programming languages specifically designed for simulation, such as GPSS.

In-depth study of the GPSS simulation language, including its syntax, features, and examples.

Analysis of real-world examples of simulation in different domains, highlighting their objectives, methodologies, and outcomes.

Concepts and techniques for designing and developing simulation models, including model types and their applications.

Methods for building mathematical models that can be used for simulation, including equation-based and algorithmic models.

A method for selecting the essential prime implicants in a Boolean function. It is used to minimize Boolean expressions and implement digital circuits.

This topic explains the concept of simulation clock and time management in discrete event simulation. It covers the techniques and methods used to manage time in simulation and modeling.

This topic introduces models of arrival processes, including Poisson processes, non-stationary Poisson processes, and batch arrivals. It explains the principles and applications of these models in simulation and modeling.

This topic covers the concept of Poisson processes, which model the arrival of events in a system. It explains the principles and applications of Poisson processes in simulation and modeling.

This topic introduces non-stationary Poisson processes, which model the arrival of events in a system with time-varying rates. It explains the principles and applications of non-stationary Poisson processes in simulation and modeling.

This topic covers the concept of batch arrivals, which model the arrival of multiple events in a system. It explains the principles and applications of batch arrivals in simulation and modeling.

This topic explains the importance of gathering statistics in simulation and modeling. It covers the techniques and methods used to collect and analyze data in simulation and modeling.

This topic introduces probability and Monte Carlo simulation, which is used to model and analyze complex systems. It explains the principles and applications of probability and Monte Carlo simulation in simulation and modeling.

Concept of query processing, including the steps involved in processing a query and the role of the query processor.

Query trees and heuristics for query optimization, including the use of query trees to represent queries and heuristics to guide optimization.

Choice of query execution plans, including the factors that influence the choice of plan and the importance of plan selection.

Cost-based optimization, including the use of cost estimates to guide optimization and the role of cost-based optimization in query processing.

This topic covers the metrics and methods used to measure the performance of queuing systems, including efficiency, effectiveness, and quality of service.

This topic explores the concept of networks of queuing systems, with a focus on computer systems and their applications.

This topic highlights the various applications of queuing systems in real-world scenarios, including manufacturing, healthcare, and transportation.

This topic introduces the concept of matrices, including their definition, notation, and basic operations. It lays the foundation for further study of matrices and their applications.

This topic covers the different types of matrices, including square matrices, diagonal matrices, identity matrices, and zero matrices. It explains their properties and characteristics.

This topic defines and explains the concept of equality of matrices, including the conditions for two matrices to be equal and the rules for comparing matrices.

This topic covers the fundamental concepts and characteristics of random numbers, including their definition, types, and properties.

This topic explores the concept of pseudo-random numbers, their generation, and their differences from true random numbers.

This topic discusses various methods and algorithms used to generate random numbers, including their strengths and weaknesses.

This topic covers the statistical tests used to evaluate the quality of random numbers, including tests for uniformity and independence.

This topic focuses on the generation of random variates from different probability distributions, including techniques and algorithms.

Introduction to vector spaces and subspaces, including their definitions and properties.

Exploration of null spaces, column spaces, and linear transformations, including their relationships and applications.

Discussion of linearly independent sets and bases, including their definitions, properties, and importance in vector spaces.

Introduction to coordinate systems, including their definition, importance, and applications in vector spaces.

Exploration of the dimension of a vector space, including its definition, properties, and importance.

Introduction to ethics and its importance in various aspects of life. Understanding the basics of ethics and its relevance in the business world.

The role of ethics in business, its impact on decision making and the importance of corporate social responsibility.

Understanding corporate social responsibility, its benefits and how it can be fostered in an organization.

Strategies and practices to promote corporate social responsibility and good business ethics in an organization.

Ways to improve business ethics, including ethical considerations in decision making and promoting a culture of ethics.

Overview of software tools used for simulation, including their features and applications.

Introduction to programming languages specifically designed for simulation, such as GPSS.

In-depth study of the GPSS simulation language, including its syntax, features, and examples.

Analysis of real-world examples of simulation in different domains, highlighting their objectives, methodologies, and outcomes.

Concepts and techniques for designing and developing simulation models, including model types and their applications.

Methods for building mathematical models that can be used for simulation, including equation-based and algorithmic models.